Kan Twitter prediktera oljemarknadens framtida avkastningar?
(2013) NEKH01 20122Department of Economics
- Abstract
- Is it possible to predict the future returns for the crude oil index by looking at the activity on Twitter? It is not possible to predict the market according to the efficient market hypothesis but earlier research on the topic states that it is possible for Twitter to predict the markets. This paper examines this phenomenon further by investigating the relationship between the market and Twitter activity during the “Arab spring”. The relationship is scrutinized by examining the number of times a particular keyword is mentioned on Twitter. The collected time series represents five keywords consisting of Egypt, Yemen, Syria, Kurdistan, and finally Pakistan. The relationship between the five time series and the future returns of crude oil... (More)
- Is it possible to predict the future returns for the crude oil index by looking at the activity on Twitter? It is not possible to predict the market according to the efficient market hypothesis but earlier research on the topic states that it is possible for Twitter to predict the markets. This paper examines this phenomenon further by investigating the relationship between the market and Twitter activity during the “Arab spring”. The relationship is scrutinized by examining the number of times a particular keyword is mentioned on Twitter. The collected time series represents five keywords consisting of Egypt, Yemen, Syria, Kurdistan, and finally Pakistan. The relationship between the five time series and the future returns of crude oil index is examined using a Vector Autoregressive-model. The model is further tested by applying a Granger-non-causality test to examine the keywords predictive power. It turns out that the keywords have a predictive capability about four days prior to the change, which also can predict the direction of the WTI-index future returns. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/3409274
- author
- Axelsson, Kristian LU
- supervisor
-
- Daniel Ekeblom LU
- Erik Wengström LU
- organization
- course
- NEKH01 20122
- year
- 2013
- type
- M2 - Bachelor Degree
- subject
- keywords
- WTI returns, Prediction, Arab spring, Twitter, Granger-causalirty
- language
- Swedish
- id
- 3409274
- date added to LUP
- 2013-02-12 15:41:06
- date last changed
- 2013-02-12 15:41:06
@misc{3409274, abstract = {{Is it possible to predict the future returns for the crude oil index by looking at the activity on Twitter? It is not possible to predict the market according to the efficient market hypothesis but earlier research on the topic states that it is possible for Twitter to predict the markets. This paper examines this phenomenon further by investigating the relationship between the market and Twitter activity during the “Arab spring”. The relationship is scrutinized by examining the number of times a particular keyword is mentioned on Twitter. The collected time series represents five keywords consisting of Egypt, Yemen, Syria, Kurdistan, and finally Pakistan. The relationship between the five time series and the future returns of crude oil index is examined using a Vector Autoregressive-model. The model is further tested by applying a Granger-non-causality test to examine the keywords predictive power. It turns out that the keywords have a predictive capability about four days prior to the change, which also can predict the direction of the WTI-index future returns.}}, author = {{Axelsson, Kristian}}, language = {{swe}}, note = {{Student Paper}}, title = {{Kan Twitter prediktera oljemarknadens framtida avkastningar?}}, year = {{2013}}, }